GAN-based Reduced Order Model for Prediction, Data Assimilation and Uncertainty Quantification

This repository is the official implementation of:

A GAN-based Reduced Order Model for Prediction, Data Assimilation and Uncertainty Quantification ICML submitted paper.

Directories:

• datasets: Datasets of the spatio-temporal spread of COVID-19 in an idealized town.
• GAN_evaluation: New way of evaluating the GAN training.
• Regularization: Regularization to improve the GAN-based Reduced Order Model.
• UQ-PredGAN: Data assimilation and uncertainty quantification using a GAN-based Reduced Order Model.
• MCMC: Comparison between the UQ-PredGAN and the Markov chain Monte Carlo (MCMC) methods.

Requirements

To install requirements:

 $ conda env create -f environment.yml 
 $ conda activate py3ml
 $ python -m ipykernel install --user --name=python3

Finally, start Jupyter:

 $ jupyter notebook

Codes

The codes and running instructions are in the directories UQ-PredGAN